Release of AI-ready multimodal functional genomics data (perturb-seq, SEC-MS, and immunofluorescence imaging) packaged with provenance graphs and rich metadata using RO-Crate/FAIRSCAPE to support AI method development and research.
Grantor
Grant Name
Grant Number
National Institutes of Health (NIH) — Bridge2AI program
Bridge2AI Functional Genomics Grand Challenge
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Composition
What do the instances represent?
Data Type
Name
Representation
Sequencing-derived data products; details provided within RO-Crate packages
perturb-seq in undifferentiated KOLF2.1J iPSCs
Single-cell perturb-seq experiment outputs
Proteomics mass spectrometry data products; details provided within RO-Crate packages
SEC-MS in KOLF2.1J iPSCs and derived cell types
Size-exclusion chromatography mass spectrometry (SEC-MS) measurements
Image data; conditions include presence/absence of vorinostat and paclitaxel
IF images in MDA-MB-468 cells +/- chemotherapy
Immunofluorescence microscopy images
Name
Experimental cell populations
Identification
Undifferentiated KOLF2.1J iPSCs
iPSC-derived NPCs
iPSC-derived neurons
iPSC-derived cardiomyocytes
Mda Mb 468 Breast Cancer Cells (with And Without Chemotherapy
vorinostat, paclitaxel)
Name
Packaging and distribution formats
Description
RO-Crate packaged datasets with provenance graphs and rich metadata
Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
This dataset is the March 2025 Data Release of Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org), the Functional Genomics Grand Challenge in the NIH Bridge2AI program. This Beta release includes perturb-seq data in undifferentiated KOLF2.1J iPSCs; SEC-MS data in undifferentiated KOLF2.1J iPSCs and iPSC-derived NPCs, neurons, and cardiomyocytes; and IF images in MDA-MB-468 breast cancer cells in the presence and absence of chemotherapy (vorinostat and paclitaxel). CM4AI output data are packaged with provenance graphs and rich metadata as AI-ready datasets in RO-Crate format using the FAIRSCAPE framework. Data presented here will be augmented regularly through the end of the project. CM4AI is a collaboration of UCSD, UCSF, Stanford, UVA, Yale, UA Birmingham, Simon Fraser University, and the Hastings Center. This data is Copyright (c) 2025 The Regents of the University of California except where otherwise noted. Spatial proteomics raw image data is copyright (c) 2025 The Board of Trustees of the Leland Stanford Junior University. Dataset licensed for reuse under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license (https://creativecommons.org/licenses/by-nc-sa/4.0/). Attribution is required to the copyright holders and the authors. Any publications referencing this data or derived products should cite the Related Publication below, as well as directly citing this data collection (2025-03-04).